fast_mpc

fast_mpc: code for fast model predictive control. fast_mpc contains two C functions, with MATLAB mex interface, that implement the fast model predictive control methods described in the paper Fast Model Predictive Control Using Online Optimization. See this paper for the precise problem formulation and meanings of the algorithm parameters.

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References in zbMATH (referenced in 58 articles )

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  1. Deng, Haoyang; Ohtsuka, Toshiyuki: ParNMPC -- a parallel optimisation toolkit for real-time nonlinear model predictive control (2022)
  2. Hosseinzadeh, Mehdi; Sinopoli, Bruno; Kolmanovsky, Ilya; Baruah, Sanjoy: ROTEC: robust to early termination command governor for systems with limited computing capacity (2022)
  3. Jiang, Canghua; Zhang, Dongming; Yuan, Chi; Teo, Kok Ley: An active set solver for constrained (H_\infty) optimal control problems with state and input constraints (2022)
  4. Ho, Vinh Thanh; Le Thi, Hoai An; Pham Dinh, Tao: DCA-based algorithms for DC fitting (2021)
  5. Magrini, Luciano A.; Oliveira Domingues, Margarete; Macau, Elbert E. N.; Kiss, István Z.: Synchronization in populations of electrochemical bursting oscillators with chaotic slow dynamics (2021)
  6. Okawa, Isao; Nonaka, Kenichiro: Linear complementarity model predictive control with limited iterations for box-constrained problems (2021)
  7. Poupard, Eduardo; Heath, William Paul; Güttel, Stefan: A Hamiltonian decomposition for fast interior-point solvers in model predictive control (2021)
  8. Son, Sang Hwan; Park, Byung Jun; Oh, Tae Hoon; Kim, Jong Woo; Lee, Jong Min: Move blocked model predictive control with guaranteed stability and improved optimality using linear interpolation of base sequences (2021)
  9. Cantoni, Michael; Farokhi, Farhad; Kerrigan, Eric; Shames, Iman: Structured computation of optimal controls for constrained cascade systems (2020)
  10. Ławryńczuk, Maciej: Nonlinear model predictive control for processes with complex dynamics: a parameterisation approach using Laguerre functions (2020)
  11. Liao-McPherson, Dominic; Kolmanovsky, Ilya: FBstab: a proximally stabilized semismooth algorithm for convex quadratic programming (2020)
  12. Magrini, Luciano A.; Oliveira Domingues, Margarete; Macau, Elbert E. N.; Kiss, István Z.: Extraction of slow and fast dynamics of multiple time scale systems using wavelet techniques (2020)
  13. Paulson, Joel A.; Buehler, Edward A.; Braatz, Richard D.; Mesbah, Ali: Stochastic model predictive control with joint chance constraints (2020)
  14. Takapoui, Reza; Moehle, Nicholas; Boyd, Stephen; Bemporad, Alberto: A simple effective heuristic for embedded mixed-integer quadratic programming (2020)
  15. Englert, Tobias; Völz, Andreas; Mesmer, Felix; Rhein, Sönke; Graichen, Knut: A software framework for embedded nonlinear model predictive control using a gradient-based augmented Lagrangian approach (GRAMPC) (2019)
  16. Morato, Marcelo Menezes; Nguyen, Manh Quan; Sename, Olivier; Dugard, Luc: Design of a fast real-time \textitLPVmodel predictive control system for semi-active suspension control of a full vehicle (2019)
  17. Otta, Pavel; Burant, Jiří; Šantin, Ondřej; Havlena, Vladimír: Newton projection with proportioning using iterative linear algebra for model predictive control with long prediction horizon (2019)
  18. Perne, Matija; Gerkšič, Samo; Pregelj, Boštjan: Soft inequality constraints in gradient method and fast gradient method for quadratic programming (2019)
  19. Qian, Hong; Yuan, Yuan; Wang, Yu; Jiang, Gaofeng; Yang, Ting: Research on pressurizer pressure control based on adaptive prediction algorithm (2019)
  20. Qu, Jingguo; Zhang, Zilong; Zhang, Huiqi: An improved predictive control model for stochastic max-plus-linear systems (2019)

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